Innovation in services

The concept of innovation is defined as “the introduction of a new product (good or service) or of one that is significantly improved, a recent process, a new marketing method, or a modern organizational system in the internal practices of a company, the organization of the work place, or if applied to external relations” (OECD, 2005). From the perspective of ^{Hidalgo et al. (2002)}, innovation is a dynamic process of the efficient use of the knowledge of an organization to develop new or improved products in a different manner. For its part, innovation in the service sector comprises new services and new manners of production or service provision, as well as significant changes in the services, their production, and the manner in which they are delivered. According to ^{Den Hertog et al. (2010)}, it is “a new service experience or service solution that may involve a new service, a new portfolio of services, and/or a new service process that individually or together define a new way of creating value for the client”.

Despite the importance of service innovation, the concept is constantly evolving. In this sense, Witell et al. analyze and characterize innovation in services according to three different perspectives: assimilation, demarcation, and synthesis. Similarly, ^{Snyder et al. (2016)}, based on an extensive and systematic review of 1,046 academic articles, explored how researchers define and use service innovation. To this end, they identify four unique categories of service innovation that emphasize the following traits: 1) degree of change, 2) exchange rate, 3) novelty, and 4) means of provision.

Traditionally, innovation management and models for its analysis have been subscribed to technological innovation and the manufacturing industry (^{Gallouj and Weisten, 1997}; ^{Chesbrough, 2011}). For ^{Tidd and Bessant (2009)}, most simply assume that such practices are equally applicable to the management of innovation in services; however, some researchers argue that services are fundamentally different. Nevertheless, the growing importance of services in global growth indices has meant that this is currently one of the priority topics of study between different disciplines related to innovation (^{Miles, 2005}; ^{Tidd and Bessant, 2009}; ^{Goffin and Mitchell, 2010}). These last two authors consider that the very characteristics of services have a direct implication in innovation management, while ^{Chesbrough (2011)} argues that the increase in services in this new stage causes these approaches to change if companies want to be successful and sustainable over time.

The process of innovation and co-creation

The service innovation process involves a high degree of interactivity between the service provider and the client (^{Zeithaml and Bitner, 2003}). From the perspective of ^{Markovic and Bagherzadeh (2018)} co-creation can generate a multitude of organizational advantages, including improved innovation performance. The participation of different actors in the co-creation of services and in innovation processes has been referenced by authors such as ^{Chesbrough (2003} and ²⁰¹¹⁾, who emphasizes the importance of external agents for innovation in their approaches to open innovation. Other authors refer to co-creation for value addition, innovation, and client participation (^{Prahalad and Ramaswamy, 2004}; ^{Vargo and Lusch, 2008}; ^{Tanev et al., 2010}; ^{Mele, Russo and Colurcio, 2010}; ^{Grönroos, 2011}; ^{Mukhat, Nazul and Yahya, 2012}; ^{Von Bischhoffshausen, Hottum and Straub, 2015}, ^{Raeisi and Lingjie, 2017}, ^{Cui, and Wu, 2017}, ^{Anning-Dorson, 2018}, ^{Mahmoud, Hinson and Anim, 2018}, ^{Cui and Wu, 2018}).

In particular, ^{Greer, Lusch, and Vargo (2016)} pose five axioms that characterize this theory: first, service is the fundamental basis of exchange; second, value is co-created by multiple actors, always including the beneficiary; third, all social and economic actors are resource integrators; fourth, value is always determined uniquely and phenomenologically by the beneficiary; and fifth, co-creation is coordinated through institutions and institutional arrangements generated by actors. Lastly, different approaches can be distinguished on the issue of value creation and its relation to co-creation, including S-D logic, service science (^{Maglio and Spohrer, 2008}), service logic, many-to-many marketing, social constructionism, and new product development or postmodernism (^{Saarijärvi and Hannu, 2013}). ^{Vargo, S. and Lusch, R. (2016} and ²⁰¹⁷⁾ have incorporated an extension or update of the dominant logic theory of service and argue that it may continue to advance over the next decade towards the further development of a general theory of the market and, even more broadly, towards a general theory of value co-creation.

Model proposal

To analyze how ICT companies manage their innovation process, a model based on the TEMAGUIDE model is proposed, elaborated by the COTEC Foundation and which incorporates a series of modules with their corresponding tools that the companies can use in the management of the innovation process (GI_TICmodel). Although this model was initially conceived for the manufacturing industry, several approximations have subsequently been carried out in order to use it in the services sector (^{COTECT, 2004}; ^{D’alvano and Hidalgo, 2011}). From this model, the areas of surveillance, learning, and implementation are maintained, and the aspects of strategy are grouped in the focus stage.

In order to identify the singularities presented by companies in the ICT services sector, two new areas have been incorporated into the model: human resources and co-creation. In the area of human resources, based on the approaches of ^{Arzola and Mejías (2007)}, the importance of knowledge in this sector and the need to incorporate training mechanisms are included. The co-creation area tries to take into account the perspective in which the different actors (clients, suppliers, universities) can actively participate in the processes of value creation and innovation. The analysis of aspects such as project development strategies and the participation of actors at different stages (ideation, product development, and implementation), the role of clients in the co-creation process (^{Von Bischhoffshausen, Hottum and Straub, 2015}), and the techniques used to carry out co-creation activities (^{Mukhat, Nazul and Yahya, 2012}) are of special interests. Figure 1 represents the proposed model.

Figure 1 Management model of innovation in ICT services. 

Definition of the sample and variables

For the validation of the GI_TIC model, a questionnaire based on contrasted studies was elaborated. For the human resources, monitoring, focusing, implementing, and learning phases, the TEMAGUIDE model (^{COTEC, 2004}) and the questionnaire used by ^{D’Alvano and Hidalgo (2012)} were considered but applied to the ICT sector. ^{Pikkarainen et al. (2011)} and ^{Von Bischhoffshausen, Hottum, and Straub (2015)} were used for the co-creation phase and the project strategy phase. The questionnaire was structured in seven modules with a total of 37 questions, the first of them on general company information (7) and the remaining six correspond to the phases of the model: Human Resources (6), Co-creation (6), Monitoring (4), Strategy and Focusing (6), Implementation (5), and Learning (3).

The survey was applied to managers of companies in the ICT sector in Costa Rica between June and August 2016. Initially, the total population to study was made up of 170 companies associated with the Chamber of Information and Communication Technologies in Costa Rica (CAMTIC), although after a pre-selection a total of 140 companies from the subsectors of information technology, technology commercialization, software development, e-commerce, digital multimedia, digital technology enabled services, and games were consolidated.

The questionnaire was sent using an electronic platform (e-survey) and the response of 47 companies (33.6% of the total) was obtained, classified in the following manner: 19 were from the subsector of information technologies (36.2%), 4 from the e-commerce subsector (8.5%), 2 from the technology commercialization subsector (4.3%), and 5 from the subsector considered as ‘others’ which includes videogames, augmented and virtual reality, regulation of ICT, and information security (10.6%). The data were processed in SPSS (version 19) and some of the graphs were from the R program version 3.3.1. Cronbach’s alpha was determined with a value of 0.877, which evidences the existence of a proper internal consistence between the variables.

ICT services innovation management index

In order to analyze the innovation capacity of the companies studied, the innovation management index in ICT services (IGIS_TIC) was defined, which is an indicator of the innovation process that companies carry out according to the model presented. This indicator varies from 0 to 100 averaging the score in the sub-index of each phase. The simple average of the sub-indices of each of the phases of the model is obtained: human resources, co-creation, monitoring, strategy and focusing, implementation, and learning (Table 1).

After creating the sub-indices, the IGIS_TIC index is obtained with their average (human resources, co-create, monitoring, focusing, implementation, and learning), the formula of which is:

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Correlations between general index and sub-indices

Figure 2 presents the matrix of correlations between the ICT services innovation management index (IGIS_TIC) and the sub-indices that make up the model. The results show that all the correlations are significant with respect to the IGIS_TIC, in all cases with a value greater than 0.7. The relations are direct and positive, which means that when the value of a certain index increases the other increases, which allows indicating and justifying the use of the indices for the development of the IGIS_TIC. In addition, it is important to point out that there are also positive relationships between the sub-indices.

Source: own elaboration based on the Innovation Management Survey of the ICT sector, Costa Rica. 2016.

Figure 2 Correlation matrix of the model 

Co-create, clients, partners-suppliers, and universities indices

The co-create index (I_COC) is obtained from the simple average of two variables, one of which results from the combination of nine possible co-creation options for each actor, derived from the three strategies and the three phases of the project execution. Also considered for the calculation was the sum of ten co-creation techniques used by companies. The mathematical definition of the index is:

Additionally, three sub-indices are generated: clients (I-CL), partner-suppliers (I_SP), and universities (I-UNIV), which are calculated in the same way as co-creation with the difference that in these cases each sub-index refers to the actors selected for this study (client, partners and suppliers, universities).

In order to analyze the significance of these sub-indices, a multiple regression was developed in relation to the innovation index (dependent variable). As a result, it was obtained that all the variables analyzed give significance to 0.1, with the value of the R² adjustment being 0.449 and the Durbin-Watson statistic being 1.939.

Figure 3 presents the matrix of correlations between the IGIS_TIC with the sub-indices I_COC, I_CL, I_SP, and I_UNIV. The results show that all the correlations are significant, that there are direct and positive relations with respect to the I_COC, and that the sub-indices of clients and suppliers have a value equal to or greater than 0.7, while in the case of universities the sub-index is lower (0.5). Nevertheless, the sub-indices with respect to the IGIS_TIC are positive, although their values are lower than 0.5. It is important to note that the relations between the actors are very low, which is not significant in the analysis since what is studied is the relationship of the company with the actors and not how they interact with each other.

Source: own elaboration based on the Innovation Management Survey of the ICT sector. Costa Rica, 2016.

Figure 3 Matrix of correlations between co-creation and innovation management 

Characteristics of the company

According to ^{Pavitt (1984)}, sectors have different priorities and characteristics that condition companies by the effects of innovation, economies of scale, and scientific intensity. With respect to size, ^{Rothwell (1985)} points out that this is a factor that has special repercussions in terms of access to resources and other factors. The use of these variables is reinforced by ^{Tidd and Bessant (2009)}, who add that these aspects may affect the management of innovation in companies.

Figure 4 shows the average value of the IGIS_TIC index and of the sub-indices that represent the capacity for co-creation. It is observed that when companies have fewer employees, i.e., between 1 and 30, the average value of the general innovation management index is below the average. This situation is the opposite when companies have more than 30 employees, which allows to conclude that the larger the company, the better its innovation management index. This scenario changes when analyzing the sub-indices related to co-creation, given that, with the exception of companies with 11 to 30 employees, in the client sub-index the average value is higher than the average, and only large companies (with more than 100 employees) have average values in the sub-indices higher than the overall average. As a complement to the above, after doing a multiple regression, taking as a dependent variable the IGIS_TIC and the variables “subsector” and “number of employees”, the data indicate that only the number of employees is significant, that is, for each employee that has a company the IGIS_TIC increases by 0.363 points.

Source: own elaboration based on the Innovation Management Survey of the ICT sector. Costa Rica, 2016.

Figure 4 Average value of the indices (IGIS_TIC and I_COC) and sub-indices (I_CL, I_SP and I_UNIV) according to the size of the company 

Subsector

When analyzing the subsector to which the company belongs, the results allow to identify that when companies belong to the software development and technology commercialization subsectors they have average values lower than the general average of the respective sub-index. When co-creation occurs with clients, the respective sub-index is greater than the average value for IT and e-commerce companies than when it occurs with suppliers and universities. Although in some subsectors the sub-indices of co-creation and actors are below average, this situation is more favorable when analyzing the general innovation index IGIS_TIC. In this case, only technology commercialization companies have a value lower than the general average (Figure 5).

Source: own elaboration based on the Innovation Management Survey of the ICT sector. Costa Rica, 2016.

Figure 5 Average value of the indices (IGIS_TIC and I_COC) and the sub-indices (I_CL, I_SP and I_UNIV) according to the subsector. 

Actors and their relation with the type of strategy

When analyzing how the indices related to co-creation and actors behave, and their relationship with the type of strategy for project development, the companies participating in the study that use each of the strategies in the vast majority of cases have indices with values higher than the average (Table 2). It is highlighted that those who use strategy have higher values in each sub-index than those who do not use it, which indicates that the companies that implement these strategies have more efficient innovation processes.

Actors and their participation in the stages of the project

The analysis of the participation of actors in the project development stages (devising, project development, implementation, and adaptation) shows that in companies that use the “project-based” strategy, clients are involved in both the devising and implementation phases. This situation varies when collaborating with partners and suppliers, where their greatest participation occurs at the product development phase. This behavior is the same as when the actor is the university (Figure 6).

Source: own elaboration based on the Innovation Management Survey of the ICT sector. Costa Rica, 2016.

Figure 6 Participation of the actors in the development phase of projects according to strategy. 

In companies that use the “out-the-box” strategy there is greater client participation in the devising and implementation phases. When collaboration takes place with partners and suppliers there is greater participation and, in the same percentage, in the devising and product development phases. For the university actor the greatest participation occurs in the development phase.

In those companies that use the “custom product development” strategy there is greater client participation in the devising and the implementation phases. When the collaboration is with the supplier-partners and with the university there is greater participation in the product development phase.

The role of the client in co-creation

According to the perspective put forward by ^{Von Bischhoffshausen, Hottum, and Straub (2015)}, clients may have different roles in the co-creation process. It is interesting to know the values obtained by analyzing the roles of the clients with respect to the innovation and co-creation indices and the client sub-index. As can be observed in Table 3, for all client roles the innovation index is higher than the average. On the other hand, when the client acts as a service specifier and quality auditor, the co-creation index is lower than the average. For the client sub-index, when the client acts as a quality auditor, it decreases in relation to the average. The fact that when a certain function or technique is used it is higher than the average is due to the fact that it has a higher value than those who do not use it.

Use of techniques and tools

The use of management techniques and tools are relevant in studies related to innovation and has been considered an important factor for the success of innovation management (^{Hidalgo and Albors, 2008}; ^{Igartua, Albors, and Hervas, 2010}; ^{Teza et al., 2016}, ^{Harrington and Voehl, 2016}; ^{Albors, Igartua, and Peiro, 2018}). For their part, ^{D’Alvano and Hidalgo (2012)} apply innovation management techniques to study the degree of development of the innovation process in service organizations (trade, health, and education). ^{Albors, J., Igartua, J., and Peiro, A. (2018)} analyze how the use of Innovation Management Techniques (IMTS) influences the innovation performance of enterprises. In the field of tools related to innovation and co-creation, ^{Füller et al. (2009)} study how consumer empowerment is through Internet-based co-creation; for their part, ^{Pallot et al. (2010)} study the use of Living Lab in research environments, from user-centered design and their experience in co-creation; while ^{Kohler et al. (2011)} analyze the consequences of the virtual co-creation experience and the use of avatars as an opportunity for companies to take advantage of the innovative potential of consumers and consumer communities.

In the study, companies were consulted about which tools are more or less used, according to the type of actor they are related to in the innovation and co-creation processes. As shown in Figure 7, the tools used are not homogeneous for the three actors and the degree of use varies according to the type of actor. However, the participatory methods tools (focus group, idea boxes, and empathic design) obtain the highest percentages of use regardless of the type of actor. When companies co-create with clients, the tool co-design and use of artefacts and prototypes is relevant (51.1%), while with the supplier actor the use of digital media is important (46.7%). In the case of the university, the methods of innovation based on user communities are among the most used. On the contrary, tools such as “Living Lab” and “people and avatars” are not widely used. The use of digital media tends to be greater when working with partners and suppliers.

Source: own elaboration based on the Innovation Management Survey of the ICT sector. Costa Rica, 2016.

Figure 7 Percentage of the use of co-creation tools according to actor.